Faced with increasing network services and number of users, requests to the servers
at those sites has signi cally skyrocketed. Moreover, most of these servers need to
run twenty-four hours a day, 7 days a week with a high reliability and availability.
Consequently, the tremendous growth of the Internet has led the requirement of multiserver
structures in order to deal with these e ectiveness issues. A much higher processing
power may be provided by a set of computational elements than by a single one, even if it
presents a powerful capacity. Additionally, the global system throughput may greatly increase
by using properly these architectures. However, to make an e cient server network
is a di cult task. This is the main goal of this dissertation.
E ciency may be increased if server network works in cooperation, distributing the
load. This is known as "load balancing". This technique may make that network is robust
and e cient, that means, overload are avoided at the same time that system resources are
well exploited.
Assuming that all servers present a same architecture, a deterministic dynamical model
is designed and a distributed control law inspired by consensus theory is developed. In
this way, the closed-loop ensures load balancing as well as asymptomatically stability.
Moreover, thanks to decentralized control, computational load is reduced and scalability
is possible. On the other hand, an attraction domain is estimated to ensure positive rates.
The e ectiveness of the distributed control is validated by simulations in Matlab &
Simulink and Network Simulator 2.